test

Author: heyronjmilton

Backend/summariser.py

@@ -64,22 +64,22 @@ async def gen_summary(file):
     return await loop.run_in_executor(None, summary, text)
 
 
-router_summariser = APIRouter()
+# router_summariser = APIRouter()
 
 
-@router_summariser.post("/get-summary")
-async def get_summary(file: UploadFile = File(...)):
-    data = await gen_summary(file)
-    return data
+# @router_summariser.post("/get-summary")
+# async def get_summary(file: UploadFile = File(...)):
+#     data = await gen_summary(file)
+#     return data
 
-@router_summariser.get("/summary-gen-progress") # route to track progress of summarization
-def get_summary_progress():
-    global progress
-    if progress is None :
-        return {"status" : "No summarisation process in progress" }
-    elif progress == 100 :
-        return {"status" : "Completed" , "value" : progress}
-    elif progress in range(0,101) :
-        return {"status" : progress}
-    else :
-        return {"invalid data detected"}
+# @router_summariser.get("/summary-gen-progress") # route to track progress of summarization
+# def get_summary_progress():
+#     global progress
+#     if progress is None :
+#         return {"status" : "No summarisation process in progress" }
+#     elif progress == 100 :
+#         return {"status" : "Completed" , "value" : progress}
+#     elif progress in range(0,101) :
+#         return {"status" : progress}
+#     else :
+#         return {"invalid data detected"}

Backend/test.py

@@ -1,10 +1,9 @@
 import openai
-import shutil
-import os
 import chardet
 from fastapi import FastAPI,UploadFile,File
 from fastapi import APIRouter
 
+openai.api_key = "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"  # Replace with your API key
 
 def detect_encoding(data):
     result = chardet.detect(data)
@@ -29,27 +28,7 @@ async def gen_questions(sorted_q: UploadFile = File(...),notebook_q: UploadFile
     decoded_reference_paper = reference_paper.decode(detect_encoding(reference_paper))
 
 
-    prompt = f"generate 10 questions that are not in reference paper but similar \nSorted Previous Year Questions:\n{decoded_sorted_questions}\n\nNotebook Question List:\n{decoded_notebook_questions}\n\nImportant Topics:\n{decoded_important_topics}\n\nReference Paper:\n{decoded_reference_paper}\n\n"
-
-
-# Generate questions using OpenAI API
-    response = openai.Completion.create(
-        engine="davinci",
-        prompt=prompt,
-        max_tokens=1000,  # Adjust the max_tokens value as per your requirement
-        temperature=0.4,  # Adjust the temperature value to control the creativity of the generated questions
-        top_p=1.0,
-        frequency_penalty=0.0,
-        presence_penalty=0.0,
-        n=5  # Adjust the 'n' value to generate more or fewer questions
-    )
-
-    # Extract the generated questions from the API response
-    generated_questions = [choice['text'].strip() for choice in response.choices]
-
-    # Print the generated questions
-    for i, question in enumerate(generated_questions):
-        print(f"Question {i+1}: {question}")   
+